{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "pygame 1.9.5\n",
      "Hello from the pygame community. https://www.pygame.org/contribute.html\n"
     ]
    }
   ],
   "source": [
    "# This notebook is for tests generation for state visualizer\n",
    "# if you cannot run this notebook in conda env check this out: https://medium.com/@nrk25693/how-to-add-your-conda-environment-to-your-jupyter-notebook-in-just-4-steps-abeab8b8d084\n",
    "from overcooked_ai_py.agents.benchmarking import AgentEvaluator\n",
    "from overcooked_ai_py.agents.agent import SampleAgent, GreedyHumanModel, RandomAgent\n",
    "from overcooked_ai_py.mdp.overcooked_mdp import OvercookedGridworld, OvercookedState, Recipe, SoupState\n",
    "from overcooked_ai_py.visualization.state_visualizer import StateVisualizer\n",
    "from overcooked_ai_py.visualization.visualization_utils import show_image_in_ipython\n",
    "from overcooked_ai_py.utils import generate_temporary_file_path\n",
    "from overcooked_ai_py.static import FONTS_DIR\n",
    "from overcooked_ai_py.mdp.layout_generator import POT\n",
    "import copy\n",
    "import pygame\n",
    "import os\n",
    "import numpy as np\n",
    "import json\n",
    "\n",
    "\n",
    "def has_cooking_timer(state, grid):\n",
    "    for obj in state.objects.values():\n",
    "        if isinstance(obj, SoupState):\n",
    "            (x_pos, y_pos) = obj.position\n",
    "            if obj._cooking_tick > 0 and grid[y_pos][x_pos] == POT:\n",
    "                print(\"found cooking object\", obj)\n",
    "                return True\n",
    "    return False\n",
    "\n",
    "\n",
    "Recipe.configure({})\n",
    "def display_and_export_to_array(test_dict):\n",
    "    test_dict = copy.deepcopy(test_dict)\n",
    "    test_dict[\"kwargs\"][\"state\"] = OvercookedState.from_dict(test_dict[\"kwargs\"][\"state\"])\n",
    "    surface =  StateVisualizer(**test_dict[\"config\"]).render_state(**test_dict[\"kwargs\"])\n",
    "    img_path = generate_temporary_file_path(\"temporary_visualization\", extension=\".png\")\n",
    "    pygame.image.save(surface, img_path)\n",
    "    print(\"check if image is okay\")\n",
    "    show_image_in_ipython(img_path)\n",
    "    return pygame.surfarray.array3d(surface)\n",
    "\n",
    "def save_test_files(test_dicts_list, test_result_arrays, json_filename):\n",
    "    for d, a in zip(test_dicts_list, test_result_arrays):\n",
    "        with open(d[\"result_array_filename\"], 'wb') as f:\n",
    "            np.save(f, a)\n",
    "    with open(json_filename, \"w\") as f:\n",
    "        json.dump(test_dicts_list, f)\n",
    "        \n",
    "DEFAULT_VALUES = {\n",
    "        \"height\": None, # if None use grid_width - NOTE: can chop down hud if hud is wider than grid\n",
    "        \"width\": None, # if None use (hud_height+grid_height)\n",
    "        \"tile_size\": 75,\n",
    "        \"window_fps\": 30,\n",
    "        \"player_colors\": ['blue', 'green'],\n",
    "        \"is_rendering_hud\": True,\n",
    "        \"hud_font_size\": 10,\n",
    "        \"hud_system_font_name\": None, # if set to None use hud_font_path\n",
    "        # needs to be overwritten with default - every pc has different pathes \"hud_font_path\": roboto_path, \n",
    "        \"hud_font_color\": (255,255,255), # white\n",
    "        \"hud_data_default_key_order\" : [\"all_orders\", \"bonus_orders\", \"time_left\", \"score\", \"potential\"],\n",
    "        \"hud_interline_size\": 10,\n",
    "        \"hud_margin_bottom\": 10,\n",
    "        \"hud_margin_top\": 10,\n",
    "        \"hud_margin_left\": 10,\n",
    "        \"hud_distance_between_orders\": 5,\n",
    "        \"hud_order_size\": 15,\n",
    "        \"is_rendering_cooking_timer\": True,\n",
    "        \"show_timer_when_cooked\": True,\n",
    "        \"cooking_timer_font_size\": 20, # # if set to None use cooking_timer_font_path\n",
    "        # needs to be overwritten with default - every pc has different pathes \"cooking_timer_font_path\": roboto_path, \n",
    "        \"cooking_timer_system_font_name\": None,\n",
    "        \"cooking_timer_font_color\": (255, 0, 0), # red\n",
    "        \"grid\": None,\n",
    "        \"background_color\": (155, 101, 0) # color of empty counter\n",
    "    }\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Avg rew: 0.00 (std: 0.00, se: 0.00); avg len: 1.00; : 100%|██████████| 1/1 [00:00<00:00, 232.98it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skipping trajectory consistency checking because MDP was recognized as variable. Trajectory consistency checking is not yet supported for variable MDPs.\n",
      "testing test_hud_1 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "testing test_hud_2 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
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      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "testing test_hud_3 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# because of inconsistent display of fonts there is no HUD tests currently used\n",
    "hud_tests = []\n",
    "hud_test_results = []\n",
    "\n",
    "mdp = OvercookedGridworld.from_layout_name(layout_name=\"cramped_room\")\n",
    "agent_eval = AgentEvaluator(env_params={\"horizon\": 1}, mdp_fn=lambda _: mdp)\n",
    "\n",
    "trajectory_random_pair = agent_eval.evaluate_random_pair(num_games=1, display=False, native_eval=True)\n",
    "grid = trajectory_random_pair[\"mdp_params\"][0][\"terrain\"]\n",
    "state = trajectory_random_pair[\"ep_states\"][0][0]\n",
    "\n",
    "config = copy.deepcopy(DEFAULT_VALUES)\n",
    "config[\"tile_size\"] = 30\n",
    "config[\"hud_font_size\"] = 20\n",
    "hud_data = {\"time_left\": 100}\n",
    "kwargs = {\"hud_data\": hud_data, \"grid\":grid, \"state\":state.to_dict()}\n",
    "\n",
    "test_hud_1 = {\"config\": config, \"kwargs\": kwargs, \n",
    "             \"comment\": \"Test simple text in hud. NOTE: failing to render stuff outside HUD also fails this test\",\n",
    "             \"result_array_filename\": \"test_hud_1.npy\"}\n",
    "print(\"testing test_hud_1 dict\")\n",
    "test_hud_1_array = display_and_export_to_array(test_hud_1)\n",
    "hud_tests.append(test_hud_1)\n",
    "hud_test_results.append(test_hud_1_array)\n",
    "\n",
    "\n",
    "config = copy.deepcopy(DEFAULT_VALUES)\n",
    "config[\"tile_size\"] = 30\n",
    "config[\"hud_font_size\"] = 20\n",
    "config[\"hud_order_size\"] = 25\n",
    "hud_data = {\"all_orders\": trajectory_random_pair[\"mdp_params\"][0][\"start_all_orders\"]}\n",
    "kwargs = {\"hud_data\": hud_data, \"grid\":grid, \"state\":state.to_dict()}\n",
    "test_hud_2 = {\"config\": config, \"kwargs\": kwargs, \n",
    "             \"comment\": \"Test simple recipes in hud. NOTE: failing to render stuff outside HUD also fails this test\",\n",
    "             \"result_array_filename\": \"test_hud_2.npy\"}\n",
    "\n",
    "print(\"testing test_hud_2 dict\")\n",
    "test_hud_2_array = display_and_export_to_array(test_hud_2)\n",
    "hud_tests.append(test_hud_2)\n",
    "hud_test_results.append(test_hud_2_array)\n",
    "\n",
    "config = copy.deepcopy(DEFAULT_VALUES)\n",
    "config[\"tile_size\"] = 30\n",
    "config[\"hud_font_size\"] = 20\n",
    "hud_data = {\"time_left\": 100, \"a\":\"a\", \"b\": \"b\", \"c\": \"c\",  \"z\":\"z\"}\n",
    "kwargs = {\"hud_data\": hud_data, \"grid\":grid, \"state\":state.to_dict()}\n",
    "test_hud_3 = {\"config\": config, \"kwargs\": kwargs, \n",
    "             \"comment\": \"Test chronology of hud based on keys NOTE: failing to render stuff outside HUD also fails this test\",\n",
    "             \"result_array_filename\": \"test_hud_3.npy\"}\n",
    "print(\"testing test_hud_3 dict\")\n",
    "test_hud_3_array = display_and_export_to_array(test_hud_3)\n",
    "hud_tests.append(test_hud_3)\n",
    "hud_test_results.append(test_hud_3_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# if all stuff above is ok run this cell\n",
    "# because of inconsistent display of fonts there is no HUD tests currently used\n",
    "save_test_files(hud_tests, hud_test_results, \"render_state_data_test_hud.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "testing test_size_1 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "testing test_size_2 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "size_tests = []\n",
    "size_test_results = []\n",
    "config = copy.deepcopy(DEFAULT_VALUES)\n",
    "config[\"tile_size\"] = 60\n",
    "kwargs = {\"hud_data\": {}, \"grid\":grid, \"state\":state.to_dict()}\n",
    "test_size_1 = {\"config\": config, \"kwargs\": kwargs, \n",
    "             \"comment\": \"Test of setting of tile_size (no hud)\",\n",
    "             \"result_array_filename\": \"test_size_1.npy\"}\n",
    "print(\"testing test_size_1 dict\")\n",
    "test_size_1_array = display_and_export_to_array(test_size_1)\n",
    "size_tests.append(test_size_1)\n",
    "size_test_results.append(test_size_1_array)\n",
    "\n",
    "config = copy.deepcopy(DEFAULT_VALUES)\n",
    "config[\"tile_size\"] = 15\n",
    "config[\"height\"] = 100\n",
    "config[\"width\"] = 100\n",
    "kwargs = {\"hud_data\": {}, \"grid\":grid, \"state\":state.to_dict()}\n",
    "test_size_2 = {\"config\": config, \"kwargs\": kwargs, \n",
    "             \"comment\": \"Test of setting of width and height (no hud)\",\n",
    "             \"result_array_filename\": \"test_size_2.npy\"}\n",
    "print(\"testing test_size_2 dict\")\n",
    "test_size_2_array = display_and_export_to_array(test_size_2)\n",
    "size_tests.append(test_size_2)\n",
    "size_test_results.append(test_size_2_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# if all stuff above is ok run this cell\n",
    "save_test_files(size_tests, size_test_results, \"render_state_data_test_sizes.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Avg rew: 0.00 (std: 0.00, se: 0.00); avg len: 1000.00; : 100%|██████████| 1/1 [00:00<00:00,  3.52it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skipping trajectory consistency checking because MDP was recognized as variable. Trajectory consistency checking is not yet supported for variable MDPs.\n",
      "found cooking object {ø1\n",
      "test_cooking_timer_1 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "rendered_cooking_timer = False\n",
    "config = copy.deepcopy(DEFAULT_VALUES)\n",
    "config[\"tile_size\"] = 45\n",
    "\n",
    "while not rendered_cooking_timer:\n",
    "    mdp = OvercookedGridworld.from_layout_name(layout_name=\"cramped_room\")\n",
    "    agent_eval = AgentEvaluator(env_params={\"horizon\": 1000}, mdp_fn=lambda _: mdp)\n",
    "    trajectory_random_pair = agent_eval.evaluate_random_pair(num_games=1, display=False, native_eval=True)\n",
    "    grid = trajectory_random_pair[\"mdp_params\"][0][\"terrain\"]\n",
    "    for state in trajectory_random_pair[\"ep_states\"][0]:\n",
    "        if not rendered_cooking_timer and has_cooking_timer(state, grid):\n",
    "            kwargs = {\"hud_data\": {}, \"grid\":grid, \"state\":state.to_dict()}\n",
    "            test_cooking_timer_1 = {\"config\": config, \"kwargs\": kwargs, \n",
    "             \"comment\": \"Test of setting rendering cooking timer\",\n",
    "             \"result_array_filename\": \"test_cooking_timer_display_1.npy\"}\n",
    "            print(\"test_cooking_timer_1 dict\")\n",
    "            test_test_cooking_timer_1_array = display_and_export_to_array(test_cooking_timer_1)\n",
    "            rendered_cooking_timer = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# if all stuff above is ok run this cell\n",
    "save_test_files([test_cooking_timer_1], [test_test_cooking_timer_1_array], \"render_state_data_test_cooking_display.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/1 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recomputing motion planner due to: [Errno 2] No such file or directory: '/Users/micah/Developer/Research/CHAI/overcooked_ai/src/overcooked_ai_py/data/planners/cramped_room_tomato_mp.pkl'\n",
      "Computing MotionPlanner to be saved in /Users/micah/Developer/Research/CHAI/overcooked_ai/src/overcooked_ai_py/data/planners/cramped_room_tomato_mp.pkl\n",
      "It took 0.03263401985168457 seconds to create mp\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Avg rew: 0.00 (std: 0.00, se: 0.00); avg len: 1001.00; : 100%|██████████| 1/1 [00:00<00:00,  2.80it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skipping trajectory consistency checking because MDP was recognized as variable. Trajectory consistency checking is not yet supported for variable MDPs.\n",
      "test_various_display_1 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_various_display_2 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_various_display_3 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_various_display_4 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_various_display_5 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_various_display_6 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_various_display_7 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_various_display_8 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_various_display_9 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_various_display_10 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# testing some states hoping it can find unexpected bugs\n",
    "various_tests = []\n",
    "various_results = []\n",
    "\n",
    "config = copy.deepcopy(DEFAULT_VALUES)\n",
    "config[\"tile_size\"] = 45\n",
    "config[\"cooking_timer_font_size\"] = 15\n",
    "mdp = OvercookedGridworld.from_layout_name(layout_name=\"cramped_room_tomato\")\n",
    "agent_eval = AgentEvaluator(env_params={\"horizon\": 1001}, mdp_fn=lambda _: mdp)\n",
    "trajectory_random_pair = agent_eval.evaluate_random_pair(num_games=1, display=False, native_eval=True)\n",
    "grid = trajectory_random_pair[\"mdp_params\"][0][\"terrain\"]\n",
    "for i in range(1, 11):\n",
    "    state = trajectory_random_pair[\"ep_states\"][0][i*100]\n",
    "    kwargs = {\"hud_data\": {}, \"grid\":grid, \"state\":state.to_dict()}\n",
    "    test_dict = {\"config\": config, \"kwargs\": kwargs, \n",
    "     \"comment\": \"Various tests\",\n",
    "     \"result_array_filename\": \"test_various_display_%d.npy\"%i}\n",
    "    print(\"test_various_display_%i dict\"%i)\n",
    "    test_array = display_and_export_to_array(test_dict)\n",
    "    various_tests.append(test_dict)\n",
    "    various_results.append(test_array)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "# if all stuff above is ok run this cell\n",
    "save_test_files(various_tests, various_results, \"render_state_data_test_various.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\r",
      "  0%|          | 0/1 [00:00<?, ?it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Recomputing motion planner due to: [Errno 2] No such file or directory: '/Users/micah/Developer/Research/CHAI/overcooked_ai/src/overcooked_ai_py/data/planners/XXOXPXX|X 1 2DX|X X   D|XX  P X|XXSXXXX_mp.pkl'\n",
      "Computing MotionPlanner to be saved in /Users/micah/Developer/Research/CHAI/overcooked_ai/src/overcooked_ai_py/data/planners/XXOXPXX|X 1 2DX|X X   D|XX  P X|XXSXXXX_mp.pkl\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Avg rew: 0.00 (std: 0.00, se: 0.00); avg len: 1001.00; : 100%|██████████| 1/1 [00:00<00:00,  2.51it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "It took 0.21285200119018555 seconds to create mp\n",
      "Skipping trajectory consistency checking because MDP was recognized as variable. Trajectory consistency checking is not yet supported for variable MDPs.\n",
      "test_generated_layout_display_1 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_generated_layout_display_2 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_generated_layout_display_3 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_generated_layout_display_4 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_generated_layout_display_5 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_generated_layout_display_6 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_generated_layout_display_7 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_generated_layout_display_8 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_generated_layout_display_9 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_generated_layout_display_10 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": "iVBORw0KGgoAAAANSUhEUgAAATsAAADhCAIAAAA4bIVtAAAOmUlEQVR4nO3db2xV5R3A8XMr3Fv6B6W2pWtBaqEgbsGEKyo4bNHEwaiiC5pojBlmFMwm8cX2Ylkm6N4sy0zM3BKLy0jEP0G2GEeRyF7Yzo1g2rKIbq5Am8L40xYELC1tL9juxXPuAztn995zzv1zzu/2+3n1895zTx+O/Pr8eO7vnCfU0mwgl6LNLSro2r7J35FAogK/BwDABTIWkGSa3wMQzEl9Gy4pU8G8+562vFX/3edVcPyvb6ggNnw+w0NE3mGOBSQhYwFJQqwVO2Svb2fOWayCoZNfqMBe39avNUvfmTWLE5350ukjKjjS+nImR4x8xBwLSELGApJIWiuef+fjlleWrn1BBTdW1qvgq8GjKji09yXLwT2d76bz0+c1xIthW32ry+Paxg0q0PVtSWVdyjOXVKU+xhddRiD+yRQ1tvs9hABhjgUkIWMBSQRUxXXR9Spo2PCW5a3z580l2VNnBlQQiVQkOljzVh57q2+HB3tVkGSteLi/18N4cumjjz5Kecw77/zY+QmfeOLXKY9ZtWqV8xNOHcyxgCRkLCCJgKo4ILzVt8fbzZ4KvdRcMtusnIcHeuPH7MzgOA1u6MtrzLGAJGQsIImAqjjatE0FemVYGxsbS/SK/WDdbuFqrVhXmJ+9/VMVuKpvdYPx0b2vJDpzbPhL5+Ox0w3PtQ3WG/oWxrua+9q5oS9PMMcCkpCxgCQC7rb7we/GVXC6f9Dy1sTERKJPFRRYfxlVV1Wq4Pc/jCT6lLdb6pzI3pkXNpmlb2l14kXsM+YNfd17XNzQR19xADHHApKQsYAkAtaK9Q104XCF5S37WrEWDocTnScJb7fUOZG9MxdXpG54Lp4d0Bv64BZzLCAJGQtIIqAq7mp9UQWNz7xteUu3SYyPm+vJkYi5DlxWVmY5uH3HlpQ/K81HRiRp6M3ewyhGzpr9G0nWikcGsn5DX/HY2Pc++eSbJ08WxmLHKyr+eM89/ykvNwyjYGJi/cGDdx07VnjlyvHy8nfuvfdkeXm2B5PHmGORAaHJyWf37685f/71Bx741bp1Y9Onb/ngg+KxMcMwHu7svPvo0TcaGn75yCNDRUVb9u2bfvWq3+MVjIxFBnzjwoX6/v6d993XU1V1uqzszZUrZ46NLejvNwxjRXf3X5YsOTxv3smbb35z5cri8fFvnTjh93gFE1AV55KrW+pc7dCRvYdR9LWZP6K20RxGcbwCHxnM1g19Fl8VFf1mzZrTs2ap/4xNm2YYxtcFBaWjozeOjh6vMBf5RwoLvywpqblw4R9ZHU1eY45FBowUFv5z7tzJeJ/Zvd3dQzNm/LumZkYsZhjG5eu+absciRTFFx3gARmLDJtz7twjHR27li+/esMNoclJwzCMUEi/OxkKFagX4YmAqri3a7cKQiHr75do01YVlFcvUMHQ4DEV2FeGezp3pfxZrh4Z4aopoq9th/Mzu6KbkI+0Wm/oy72bhod/9OGHf7vtts4FCwzDUKkZui5FQ5OTE9clMNxijkXGFMZiW/bt662s3L18uXrlciRiGEbxdWVwydjY5UjCOzGQEhmLzLjh66+f3b9/uLDwD/ffPxmfRYdnzLhYVHTroHnTVenoaNnw8CnbV+VwTkBVrNnLWieFritJHhlh56opwtWZ5Zmc/H5bW/mlS79dvbpkdFS9NlFQMFRU9PdFi+7/7LOTZWVnZ858uLPz0owZn8+d6+9gRZOUsQismy5fvqunxzCMbbt36xfPlZT87MknW6PRyNWrT338sep5enX16ivT+FvnHdcOGXCxuHhT8/+//X2ioGD38uX6X7ZIExnrXX7s0JEED38IIFaeAEnIWEASqmLvfNmhA1MccywgCRkLSBKU5xUvaWrxewgprOg/lNkTHqhamtkT5qvDrdYHetTd+bgKovGdWW6srFeBfv5e196XVNDraYPvwGKOBSQhYwFJWCuGGHVL16ugccNbKtCP5jt1ZkAFkUiF5RgtP8pj5lhAEjIWkISq2Cm9tJvmojFLxJ5FH9qmAl0MO9nyW68nUxUDyDUyFpDEUVU8P/6FtbY08TfXh+LfXGs9eVGNwHf6L5t972+7WCymgvKq+iyOKeeYYwFJyFhAkmRVcV3U/MK6wfZldJJvru0Ha/lRHncYXel8/IrBWrFH9r2/nWz5bd/pW3RbMnMsIAkZC0hCB0UGLNtk1skdLdFEryB99r2/nWz5rfdzyY+2ZOZYQBIyFpAkWVUcbdqmAl08aE76OTXdbiF6rXjRsgdVMKvK+tiOiY1mcLGvTQUdLT/J0bCmEvsuh042N9RbvTy29XMViG5LZo4FJCFjAUmSVcWu2jg13c+piW7srJi7SAUzK8wd2U6cOJHo4Jq5K1Vw88KHVfDlkT9nc3RTlC50XW1umB9tycyxgCRkLCBJsqrY3sapOenntJ9Horol31bBqdNnUh585ox5TG3Dzy2BdnAPG8ZljKsO4Uy1JfuLORaQhIwFJElWFdvbODUn/Zya/i5bouGLZ1UwsO9RFVR850+JDtbHzNnYke2BTWXeOoS/aHtVBYsbn7N8yklbckAwxwKSkLGAJNxtl8K/DuxRwd3xQvfChQsquHTpkgpKS0tVcAvFcE54e3DxnNvNzvD2HU+Z53HTlhwQzLGAJGQsIEmyqth+c5PmpJzQglZXuDI5OakC3flwz0Pm3XazZs3yZ0xTXpodwt7akgOCORaQhIwFJHG0VmwvHiSWE5liL49dvYX05UeHsDfMsYAkZCwgCR0Urq1Ytzkebra8deD911RQUJDwV6E+Bp6l+eBi0ZhjAUnIWEASqmLXnJS1lL5ZleaDi0VjjgUkIWMBSUIt1q/6/bGkqcXvIRiGYRxu3eT3EAwjMFcD17P/3fBl52jmWEASMhaQhLViwB1/d45mjgUkIWMBSaiKAXe8PRcuUztHM8cCkpCxgCRUxYA7/u4czRwLSELGApJQFQPuZOq5cN7akpljAUnIWECSdKviaLN5X1jX9kDcp+YvrsZUkOZz4dJsS2aOBSQhYwFJ3FXF4RJziq9teNry1sK1z6ugr/0NFcSGz6c3tqDjakxNaT4X7rGtn6vAW1sycywgCRkLSOKuKq5tNMu/0urFlrdKa8xXbl21QQXde15Ob2xBx9WY4rztHJ1mWzJzLCAJGQtI4q4qLq6oS33M7NTH5AeuBhRXHcJptiUzxwKSkLGAJO6q4pGzvSqwr45eO2agN60RycHVmOK8dQh/0faqChY3Pmf5lJO2ZOZYQBIyFpDEXVXc12Z2yermgeJKcy10ZNAs/46378zQ2IKOqzHFeXtw8ZzbH1RB+46nzPO4aUtmjgUkIWMBSdxVxfqWsSOtr2RhMMJwNaa4NDuEvbUlM8cCkpCxgCQ8rxjwKFMPLnaFORaQhIwFJKEqBjxK88HF3jDHApKQsYAkVMWAR2k+uNgb5lhAEjIWkCTU0uz3EIJkSVOL30MIkMOtgdihz8n/lBV7Qxn5WQfWTiZ6KyBXgzkWkISMBSQhYwFJyFhAEjIWkIQOCuQDvcbrbdE4yRJx0DDHApKQsYAkVMVIqMsIRHvNEr8H4Nz8+CZ32tLEu90diu92p/V0vpvyRzDHApKQsYAkVMVIbfv27ZZX6uvrs/1DV61a5eFTHVHrUJ24Ymz08CmtLmpuctcQ38BOS7Lbnf1gLUl5zBwLSELGApLkSVUcbTZvyOraHohbouC7ZZu6VNDREvV3JJnFHAtIQsYCkoisisMl5qNfaxuetry1cO3zKuhrN7dj1jvQIY9N73/d8koui+Fo0zYV6JVhzcke0Jput2CtGMgTZCwgiciquLbRLIZLqxdb3iqtMV+5ddUGFXTveTlnA8tXzc2BaDBO4kqV2QJhL49zwNXWz5reA1rTm0EnwRwLSELGApKIrIqLK+pSHzM79TEQanq1GUyOm0+cCIXMh0gsW2c2TkxMTDg/4cE9XrqRNfvWz5qTPaDt50mCORaQhIwFJBFZFY+c7VWBfa342jEDvbkaDnLtWjEcsT5Rrbt7jwpisWEVhMMl2R6Pfetnzcke0JqTzaCZYwFJyFhAEpFVcV+b2TOsWymKK82V4ZFBsxg+3r4z9wNDjiR+JvFQ2zYVhDd25GYsOcYcC0hCxgKSiKyK9Q10R1pf8Xck8MXVc+YS8bTy+KKxYb4S9aMY7u3abQ4jZJ0Co01bVVBevUAFQ4PHVGBfGe7p3JXyZzHHApKQsYAkIqtiQNHlsWbvEL7noYS3CqbZTmxnL2udFLquMMcCkpCxgCRUxUgoamS4aPSqxcNnVqzbHA83JzrmwPuveRqPn5hjAUnIWEASqmLkJ4kVrxPMsYAkZCwgCVXx/7g4/Ra/h2AYhnHivTV+DyFADreyX+E1zLGAJGQsIAkZC0hCxgKSkLGAJGQsIAkZC0hCxgKS0EEh1fw7H7e8snTtCyrQGxDrvdIO7X3JcnBP57vZHF2uTZ2rwRwLSELGApJQFQtTF12vgoYNbyU6Rm91XFq5KOXBggpCuyRXQ28qd+rMgAoikYpEB2vBvxrMsYAkZCwgCRkLSELGApKQsYAkrBULE23alvKYTz/9gwruuOOZRMfoBoPgr44moa+GXhnWxsbGEr1iP1jQ1WCOBSQhYwFJqIqF0V2yE7a3dDFsf8VeHuvziKb/FKf7B51/KhaLWV4prxJzNZhjAUnIWEASqmJh9C1jumdY06Wvk7VifR7R9J8iHK6wvGVfK9bC4XCi8wQfcywgCRkLSEJVLExX64sqaHzm7UTHJCmGtUN7f5GxMfknydXQbRLj4+MqiEQiKigrK7Mc3L5jS7aGmGnMsYAkZCwgCRkLSELGApKQsYAkrBUL09u1WwWhkPW3bbRpqwpmVi5QwdDgMRXoNVWtp3NXtoaYQ06uRnm19WrYV4YFXQ3mWEASMhaQJNTS7PcQguSWR/f5PQTDMIwT763xewgIKOZYQBIyFpCEjAUkIWMBSchYQBIyFpCEjAUkIWMBSf4LB1PDCnsBrsYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from overcooked_ai_py.mdp.layout_generator import LayoutGenerator\n",
    "# testing some states hoping it can find unexpected bugs\n",
    "generated_layout_tests = []\n",
    "generated_layout_results = []\n",
    "\n",
    "config = copy.deepcopy(DEFAULT_VALUES)\n",
    "config[\"tile_size\"] = 45\n",
    "config[\"cooking_timer_font_size\"] = 15\n",
    "\n",
    "DEFAULT_MDP_GEN_PARAMS = {\n",
    "    \"inner_shape\": (7, 5),\n",
    "    \"prop_empty\": 0.7,\n",
    "    \"prop_feats\": 0.4,\n",
    "    \"start_all_orders\" : [\n",
    "        { \"ingredients\" : [\"onion\", \"onion\", \"onion\"]}\n",
    "    ],\n",
    "    \"recipe_values\" : [20],\n",
    "    \"recipe_times\" : [20],\n",
    "    \"display\": False\n",
    "}\n",
    "\n",
    "mdp_fn = LayoutGenerator.mdp_gen_fn_from_dict(DEFAULT_MDP_GEN_PARAMS, outer_shape=(7, 5))\n",
    "\n",
    "agent_eval = AgentEvaluator({\"horizon\": 1001}, mdp_fn)\n",
    "trajectory_random_pair = agent_eval.evaluate_random_pair(num_games=1, display=False, native_eval=True)\n",
    "grid = trajectory_random_pair[\"mdp_params\"][0][\"terrain\"]\n",
    "for i in range(1, 11):\n",
    "    state = trajectory_random_pair[\"ep_states\"][0][i*100]\n",
    "    kwargs = {\"hud_data\": {}, \"grid\":grid, \"state\":state.to_dict()}\n",
    "    test_dict = {\"config\": config, \"kwargs\": kwargs, \n",
    "     \"comment\": \"Various tests on generated layout\",\n",
    "     \"result_array_filename\": \"test_generated_layout_display_%d.npy\"%i}\n",
    "    print(\"test_generated_layout_display_%i dict\"%i)\n",
    "    test_array = display_and_export_to_array(test_dict)\n",
    "    generated_layout_tests.append(test_dict)\n",
    "    generated_layout_results.append(test_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# if all stuff above is ok run this cell\n",
    "save_test_files(generated_layout_tests, generated_layout_results, \"render_state_data_test_generated_layout.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Avg rew: 0.00 (std: 0.00, se: 0.00); avg len: 1001.00; : 100%|██████████| 1/1 [00:00<00:00,  3.96it/s]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Skipping trajectory consistency checking because MDP was recognized as variable. Trajectory consistency checking is not yet supported for variable MDPs.\n",
      "Computing MediumLevelActionManager\n",
      "Loaded MediumLevelActionManager from /Users/micah/Developer/Research/CHAI/overcooked_ai/src/overcooked_ai_py/data/planners/cramped_room_am.pkl\n",
      "test_action_probs_display_1 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_action_probs_display_2 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_action_probs_display_3 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_action_probs_display_4 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": 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4j4j4AB6PT1VViLkHhcuSgtk2Oztbp9Pduvo7XrtGrUqYG5G8FAmUaCO550d5JHJONARtbW1FTPTrZkgQUiTXIylMdHF0S+rkUAs3Px8C3tS9iBxof3vDfJv3EnfTEB6K7ph02sA4itAOahShnejOudtck41g6jWqh+iTqB7+80NU59xJpw2MowjtoEYR2oluXJ/gaXkkiZBOGyk1h7+FfNL5JW9FXq1S/tlGvZPnzQ1xwVyP0A5qFKEd1ChCO6hRhHZQowjtoEYR2kGNxk7X7b7wnQAAIPBZq9RzQzpwfjR2rLali1e69u6qCVG1YWp2XvCk3dRzQzpQo/Fyd2Do7sCQSsH/Tfp8vtBHc6SkG1KAuV4c3B7+KYy80inPlRvighqNnVMvH4yw58ljEhZFosQN6cBcHzsyGdPe2mx9utTVHXTU0ri7NsKjF5LdDenAOBovBXnZ7a3NKiX/v10uk7W3NidMGZS4IQUYR8Xhm0dfAoBPb9xZXnUyAK1HmjTqLTgSnBI3CCFq5EYFalRMXj7UuNUuAFDjhlhgrkdoB+MoIg7cM3cVR/g1cmtOsDVyx2I6MBHjKEI7qFGEdjDXI+JQ0cKm+KwSfi2drI3qOtuOskfXPfo4igMTMY4itIMaRWgHcz0iDhmF4WvkZujC9wkE4yhCO6hRhHYw1yPisDzHFscLHNdv9pnFGrlIKoIaRWgHcz0iDmOd7Fo8N5mfsXEazrKFXyM3KjCOIrSDGkVoB3M9Ig7cdruhDpFr5GIcRWgHNYrQDmoUoR3UKEI7qFGEdlCjCO2gRhHaQY0itIMaRWgHNYrQDmoUoR1a1usDj0qvbPw2MRpOvEOMnKJqYixahonRc/nHxBi985HkLiYQ4+k/bLULFIFxFKEd1ChCO7Tkeo7Kva8Qo+WNXxFjYYHd9GWeniWGWl3I68ORYkkfAYyjCP2gRhHaoS7XN5z6ITG4FO90Onl9uBauDzf2x1yfemAcRWgHNYrQDnW5npuon5qxhO3sdruJodVXS+gTsqVgHEVoBzWK0A51uZ5bi1ep2In6wHE9h0ql4r2L43le7k8xMI4itIMaRWiHulzf0/EjYrR890NicBP1LpeLGGq1mhj5+ezZatcufI8YuNyfemAcRWgHNYrQDnW5frTnt8RgGPb/p+Hku8TQllQRY8kyQgwuxT++8xti/NW7A8TA5f6UAeMoQjuoUYR2qMv1HFz65oxIwOX+1APjKEI7qFGEdujN9RxRrbyLtdyP0APGUYR2UKMI7dCb62NbeX/Y+XNibG/5B967IlnuRygE4yhCO6hRhHbozfWxPWhfuqOVGNcuvMpeJ5rlfoRCMI4itIMaRWiH3lwf58p7bMv9CIVgHEVoBzWK0A69uR5X3hECxlGEdlCjCO3Qm+vjfNAeSRkwjiK0gxpFaIfeXB/ng/ZIyoBxFKEd1ChCO/8P2Twv3vlqzZMAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_action_probs_display_5 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_action_probs_display_6 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_action_probs_display_7 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_action_probs_display_8 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_action_probs_display_9 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "test_action_probs_display_10 dict\n",
      "check if image is okay\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "action_probs_tests = []\n",
    "action_probs_results = []\n",
    "config = copy.deepcopy(DEFAULT_VALUES)\n",
    "config[\"tile_size\"] = 45\n",
    "config[\"cooking_timer_font_size\"] = 15\n",
    "mdp = OvercookedGridworld.from_layout_name(layout_name=\"cramped_room\")\n",
    "agent_eval = AgentEvaluator(env_params={\"horizon\": 1001}, mdp_fn=lambda _: mdp)\n",
    "trajectory_random_pair = agent_eval.evaluate_random_pair(num_games=1, display=False, native_eval=True)\n",
    "grid = trajectory_random_pair[\"mdp_params\"][0][\"terrain\"]\n",
    "\n",
    "agent1 = SampleAgent([GreedyHumanModel(mlam=agent_eval.env.mlam),\n",
    "                      RandomAgent(all_actions=True),\n",
    "                      RandomAgent(all_actions=False)])\n",
    "agent1.agents[0].set_agent_index(0)\n",
    "agent2 = SampleAgent([GreedyHumanModel(mlam=agent_eval.env.mlam),\n",
    "                      RandomAgent(all_actions=True),\n",
    "                      RandomAgent(all_actions=False)])\n",
    "agent2.agents[0].set_agent_index(1)\n",
    "\n",
    "for i in range(1, 11):\n",
    "    state = trajectory_random_pair[\"ep_states\"][0][i*100]\n",
    "    action_probs = [list(agent1.action(state)[1][\"action_probs\"]), list(agent2.action(state)[1][\"action_probs\"])]\n",
    "    kwargs = {\"hud_data\": {}, \"grid\":grid, \"state\":state.to_dict(), \"action_probs\":action_probs}\n",
    "    test_dict = {\"config\": config, \"kwargs\": kwargs, \n",
    "     \"comment\": \"Action probs tests\",\n",
    "     \"result_array_filename\": \"test_action_probs_display_%d.npy\"%i}\n",
    "    print(\"test_action_probs_display_%i dict\"%i)\n",
    "    test_array = display_and_export_to_array(test_dict)\n",
    "    action_probs_tests.append(test_dict)\n",
    "    action_probs_results.append(test_array)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# if all stuff above is ok run this cell\n",
    "save_test_files(action_probs_tests, action_probs_results, \"render_state_data_test_action_probs_display.json\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.7"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
